This course is designed to provide a comprehensive understanding of AWS services used for governance, monitoring, security, compliance, automation, and cost management. Learners will explore how organizations maintain secure, compliant, and cost-efficient cloud environments while ensuring operational visibility and effective resource management.

The course begins with monitoring, auditing, and governance services that help organizations track resource activity, maintain compliance, and gain operational insights. Learners will then explore AWS identity, security, and compliance services that protect cloud workloads, manage access controls, safeguard sensitive data, and support regulatory requirements. Finally, the course covers management, automation, and cost optimization services that help organizations automate infrastructure management, govern multi-account environments, and optimize cloud spending. This course is structured into multiple modules, each featuring lessons and video lectures that provide both theoretical knowledge and practical insights into AWS governance and management services. Participants will engage with approximately 2–3 hours of instructional content, ensuring both conceptual understanding and practical application. To reinforce learning, graded and ungraded assignments are included within each module to help learners apply governance, security, and cost management concepts in real-world cloud environments. Module 1: Monitoring, Auditing & Governance Services Module 2: Identity, Security & Compliance Module 3: Management, Automation & Cost Optimization At the end of the course, learners will learn * Understand how AWS services support monitoring, auditing, governance, security, compliance, and cost optimization. * Implement identity and access management best practices to secure AWS resources. * Use AWS management and cost optimization services to improve operational efficiency and cloud governance. This course is for Team Managers, Cloud Practitioners, IT Professionals, Solutions Architects, Security Engineers, Operations Engineers, Compliance Professionals, Project Managers, and learners seeking to understand AWS governance and operational best practices.

This course is designed to provide a comprehensive introduction to AWS Artificial Intelligence (AI) Services, enabling learners to understand how organizations use managed AI solutions to add intelligence to applications without building machine learning models from scratch. Participants will explore AWS services that support natural language processing, speech recognition, conversational AI, computer vision, intelligent search, personalization, and document intelligence.

The course begins by introducing AI services for language processing and conversational experiences. Learners will explore services that analyze text, translate languages, convert speech to text, generate natural-sounding speech, and build intelligent chatbots. The course then progresses to AI services for computer vision, intelligent search, personalization, and human-in-the-loop workflows, helping learners understand how organizations extract insights from images and documents, deliver personalized recommendations, and improve AI outcomes through human review processes. This course is structured into multiple modules, each featuring lessons and video lectures that provide both theoretical knowledge and practical demonstrations of AWS AI services. Participants will engage with approximately 2–3 hours of instructional content, ensuring both conceptual understanding and practical application. To reinforce learning, graded and ungraded assignments are included within each module to help learners apply AI concepts in real-world business scenarios. Module 1: AI Services for Language & Conversational AI Module 2: AI Services for Vision, Search & Personalization At the end of the course, learners will learn * Understand the capabilities and use cases of AWS managed AI services for language processing, speech AI, computer vision, intelligent search, and personalization. * Identify the appropriate AWS AI service for different business and technical requirements. * Explain how organizations use AWS AI services to build intelligent applications and improve customer experiences. This course is for Cloud Practitioners, Team Managers, Business Analysts, Solutions Architects, Developers, Data Professionals, AI Enthusiasts, and learners interested in understanding AWS AI services and their business applications.

This course is designed to provide a comprehensive introduction to Generative AI and the AWS services that enable organizations to build, customize, and deploy AI-powered applications. Learners will explore the foundational concepts of generative AI, understand how foundation models work, and discover how businesses are using these technologies to transform customer experiences, automate processes, and drive innovation.

The course begins by introducing the core concepts of generative AI, including foundation models, model lifecycles, business use cases, challenges, and evaluation metrics. Learners will then explore Amazon Q and Amazon Bedrock, gaining an understanding of how AWS simplifies the development of generative AI applications through managed services and access to multiple foundation models. Finally, the course covers advanced concepts such as Retrieval-Augmented Generation (RAG), knowledge bases, AI agents, guardrails, and model evaluation, enabling learners to understand how modern AI applications are built and governed. This course is structured into multiple modules, each featuring lessons and video lectures that provide theoretical knowledge and practical demonstrations. Participants will engage with approximately 2–3 hours of instructional content, ensuring both conceptual understanding and practical application. To reinforce learning, graded and ungraded assignments are included within each module to help learners apply generative AI concepts in real-world scenarios. Module 1: Generative AI Foundations Module 2: Amazon Q & Amazon Bedrock Fundamentals Module 3: RAG, Knowledge Bases & AI Agents ## At the end of the course, learners will learn * Understand the core concepts, terminology, use cases, and business value of Generative AI and Foundation Models. * Explore Amazon Q, Amazon Bedrock, and foundation model selection strategies to build AI-powered applications on AWS. * Understand Retrieval-Augmented Generation (RAG), knowledge bases, AI agents, guardrails, and evaluation techniques for developing trustworthy generative AI solutions. This course is for Team Managers, Business Leaders, Cloud Practitioners, Solutions Architects, Developers, Data Engineers, AI Enthusiasts, Technical Consultants, and professionals interested in understanding Generative AI on AWS.